Question

I frequently want to parallelize a task that relies on a non-threadsafe shared resource. Consider the following non-threadsafe class. I want to do a map over a data: Vector[String].

class Processor { def apply: String => String }

Basically, I want to create n threads, each with an instance of Processor and a partition of the data. Scala parallel collections have spoiled me into thinking the parallelization should be dirt simple. However, they don’t seem well suited for this problem. Yes, I can use actors but Scala actors might become deprecated and Akka seems like overkill.

The first thing that comes to mind is to have a synchronized map Thread -> Processor and then use parallel collections, looking up my Processor in this thread-safe map. Is there a better way?

Answer 1

Instead of building your own synchronized map, you can use ThreadLocal. That will guarantee a unique Processor per thread.

val processors = new ThreadLocal[Processor] {
  def initialValue() = new Processor
}

data.par.map(x => processors.get.apply(x))